心理追凶

Chinese scientists develop ‘brain-reading’ AI model to help predict depression risk, may inspire future emotional-perception humanoids_我的网站

A |     文|小周笔谈编辑| 小周笔谈——【·前言·】——一个普通农民，为了给自己的农用收割机加点柴油，却被罚款30000元，他到底有什么错？故事发生在安徽寿县一个顾姓的男子身上，他是个地地道道的农民。    

Brain-reading AI model reveals how different brain regions are linked to cognitive functions. Photo: Courtesy of Lu Han
Chinese scientists have developed a “brain-reading” AI model that could help predict the risk of depression among adolescents up to four years in advance by analyzing how humans respond to facial expressions, a technology expected to inspire future development of embodied intelligent humanoids capable of perceiving human emotion and thoughts through nuanced facial cues. 
WHO data show that around 332 million people worldwide have depression, about one-third of whom have treatment-resistant forms of the condition. In China, an estimated 95 million people suffer from depression, National Business Daily reported, citing statistics from the China Mental Health Survey. 
Using data from a population-based longitudinal adolescent cohort recruited across several European countries, the research team led by Lu Han, assistant professor at the School of Artificial Intelligence, Shenzhen University, has built an AI model that predicted which 19-year-olds were more likely to develop depression at the age of 23. The predictions were backed up by an independent clinical cohort of individuals with depression. The team’s paper was published in the journal Science Advances this month.
According to Lu, the study used brain scans taken at age 19 to predict depression-related symptoms at age 23. The study focuses on adolescence because the transition from adolescence to early adulthood is a key developmental period when depressive symptoms can increase rapidly. The earlier risks are identified, the greater the opportunity for prevention, Lu told the Global Times on Monday, adding that the findings need to be further validated in middle-aged and older adults and across different ethnic groups in future research. 
In this study, the researchers analyzed data from adolescents in the IMAGEN, a population-based longitudinal cohort recruited across several European countries. At age 19, participants underwent an fMRI emotional-face task, and their emotional symptoms were assessed using standardized questionnaires. Genetic data obtained from blood samples were also analyzed, and participants were followed up at age 23. The researchers examined whether neural representations of angry faces at age 19 were associated with emotional symptoms and could predict elevated emotional symptoms four years later.
According to Lu, people without depression can more easily distinguish emotional changes based on others’ facial expressions and respond accordingly – for example, responding with friendliness to a smiling expression. But people with depression cannot do this, and are more likely to assume people are angry with them. 
A brain-aligned deep-learning model developed by Lu’s team suggested that those participants whose brains were less able to distinguish between different facial emotions and tended to perceive others as angry were more likely to develop symptoms of depression and anxiety in adulthood. 
The hypothesis that adolescents at risk of depression may respond differently to other people’s facial expressions than those without such risk based on the negative information processing bias long observed in depression research: people at risk of depression are more likely to notice, interpret, or remember negative social information, Lu said. 
The researchers focused on angry facial expressions because they signal social threat and rejection, which are closely linked to interpersonal difficulties and negativity bias associated with depression. They hope to further understand how this bias develops within the visual system. 
Building on this, they created a deep learning model, which mimics how the brain processes visual information, to predict how the brain encodes abstract emotional concepts such as anger.
They found that 19-year-olds whose response to facial expressions was skewed in favour of negative emotions or memories were the most likely to develop some form of depression.
Based on these findings, Lu’s team then developed a marker that can identify possible warning signs. 
According to Lu, the study found that the computational biomarker was linked to the depression-related variant rs11123030 and polygenic risk for depression, suggesting that genetic susceptibility may affect emotional perception. It also provided predictive information beyond family stress and socioeconomic factors, complementing rather than replacing environmental risk factors. Therefore, depression is neither purely genetic nor purely psychological, but a complex mental disorder arising from the interplay of genetic susceptibility, brain development, emotional and cognitive processes, and life experiences. 
According to Lu, the study is also expected to advance AI by aligning deep neural networks with human brain activity and using parameter perturbations to probe neural mechanisms, allowing models to both predict and explain how biases may arise. 
The findings suggest that future affective computing and embodied AI should go beyond simply labeling facial expressions, incorporating visual details while preventing prior assumptions from overriding real-time sensory input, Lu said, adding that the findings could provide valuable insights for developing more interpretable robotic perception systems that more closely emulate the way humans process emotions.
。为了在秋收时节给自己的收割机加点柴油，便用皮卡车从加油站载着柴油给机油满上，但是哪里知道，等待他的却是一张30000元的罚单。视频解说视频加载中...事情原委事情是这样的，2024年11月，安徽寿县村民顾先生农忙时农机柴油用完了，眼看稻谷已成成熟，必须抢在好天气的时候给他收割了。于是顾先生便开着自己的皮卡车到镇上加油站用桶购买了一些柴油，但在运输回家的路上，便被执法人员给堵住了，执法人员以顾先生在没有许可的情况下，竟然私自运输柴油，已经涉嫌“非法运输危险品”，现场开具了一张30000元的罚单。顾先生现场便懵了，他却不知自己已经成了执法人员眼中的“危险分子”。这笔罚款对顾先生来说，就算是把家里掏空了也凑不齐。为了筹集这3万元，他不得不含泪将自己好不容易种植的粮食卖掉，但还不够，还到处向亲戚和邻里借钱，总算筹满了这30000元罚单。亲戚朋友都为他感到叹息，自己也觉得今年没有了奔头，自己脸朝黄土背朝天的忙活了一年，到头来却是一场空。这一切，他只是为了给一台机器加油。谁能想到，农民的这一“日常操作”，居然成了法律“口中的重罪”？事后，顾先生从被人口中得知，这种事情可以向当地政府部门申请行政复议。顾先生向安徽寿县相关部门提交了行政复议，经过几番努力，最终撤销了这个合理又不合理的罚单，顾先生成功拿回自己的30000元。顾先生的故事看似结束了，但背后的问题远远没有解决。这不仅仅是一个“罚款与复议”的故事，它背后隐藏着的，是关于农民、法律和实际需求之间错综复杂的关系。

B | 它暴露了现代农业中一个几乎无人关注的巨大矛盾：农民与法律之间的沟通鸿沟，以及在实际操作中法律对农民生计的忽视。收割机是农业现代化的重要体现，也是农民最常用的收割工具，柴油也是日常作业的必需品。当这些“日常”行为触及到交通安全、危险品运输等相关法律时，农民常常是毫无招架之力的。法律对于城市和农村的管理差异，导致了许多农民在面对规定时，无意中成了“违法者”。我们的法律是否真正走进了农村，是否切切实实为农民提供便利？顾先生为了给收割机加油，却付出了一年的努力，他能从困境中走出来，也是因为有人告诉他可以这么做，但是其他人呢？也许，这只是一个小小的插曲，但它揭开了更大社会问题的冰山一角……网友热议在顾先生的案件曝光之后，很多网友和媒体开始关注这一事件，纷纷为顾先生叫屈。

C | 有人说：这个问题是小事，问题是耽误农活，严重破坏农业生产，应当追究违法者敲诈勒索严重破坏农业生产犯罪行为法律责任。有人说：官方不是说罚款合法合规吗？既然合法合规，罚款怎么能复议成功？是迫于舆论压力还是执法人员执法犯法？请给大众一个交代。有人说：此次案件 具有广泛的参考意义 也就是说皮卡车在合法条件装载农业生产所需的燃油是合法合规也有人说：首先 权力不能滥用！其次，执法为民不能只是“口号”或者“幌子”。

D | 此事性质就是以“执法为民、公正执法”为“幌子”变成“刁难”百姓为事实！小编总结顾先生的故事只是众多农民困境中的一例缩影。实际上，许多农民面临的，不仅仅是法律层面的难题，更是一场在“遵守法规”与“维持生计”之间的艰难博弈。

E | 在这场博弈中，法律看似严苛且不容妥协，但对农民来说，却是生存的底线。为了生计，他们不得不在法律的框架内努力寻找平衡点。我们亟需加强对农村法律问题的关注，特别是农业生产中的“灰色地带”。如何在保障安全的同时，又不让农民因严格法律条文而无法维持生计，这是一道亟待解答的难题。毕竟，农民是现代农业生产的核心力量，他们的福祉不仅关系到家庭生活，更关乎国家的粮食安全与社会的稳定。顾先生能够成功撤销处罚的背后，或许值得我们深思：如何才能让法律真正成为农民的“保护伞”，而非“绊脚石”？也许，是时候对相关法律进行更深刻的修订和更新，真正做到既符合现实需求，又不失公平公正。

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